The technology described herein relates to the processing of a set of weight values for an artificial neural network.
Artificial neural networks have many different applications, often related to classification tasks such as image or speech recognition. Artificial neural networks typically comprise an input layer that receives an input, one or more intermediate layers (such as activation layers, convolutional layers, pooling layers, fully connected layers, etc.), and an output layer that provides a result. Weight values are typically applied at layers, or at interconnections between layers, to produce a result from an input to the artificial neural network.
For example, in the case of image recognition, the input to the artificial neural network typically comprises a set of (e.g. colour or luminance) input values that represent an image and the result typically comprises one or more values that indicate whether or not a particular feature is deemed by the artificial neural network to be present in the image.
The Applicants believe that there remains scope for improved arrangements when processing weight values for artificial neural networks.
The drawings show elements of a data processing apparatus and system that are relevant to embodiments of the technology described herein. As will be appreciated by those skilled in the art there may be other elements of the data processing apparatus and system that are not illustrated in the drawings. It should also be noted here that the drawings are only schematic, and that, for example, in practice the shown elements may share significant hardware circuits, even though they are shown schematically as separate elements in the drawings. Like reference numerals are used for like elements where appropriate in the drawings.